Sioshansi F.P. Smart Grid: Integrating Renewable, Distributed & Efficient Energy
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Table 19.3
Number of Hours During Each Period When No Market Fixing Would Have Been
Obtained, as a Function of the Number of EVS in Service. Scenario 1 for
Recharging Batteries, Scenario LLL for the Generation Fleet
Not V2G, LLL 0 0.4 M 0.8 M 1.2 M 1.6 M 2 M
Peak Winter 0 0 0 0 0 0
Peak Summer 0 0 0 0 0 0
Off-peak Winter 0 0.02 0.78 5.62 20.48 46.5
Off-peak Summer 0 0 0 0.06 0.94 4.40
Table 19.4
Number of Hours During Each Period When No Market Fixing Would Have Been
Obtained, as a Function of the Number of EVS in Service. Scenario 2 for
Recharging Batteries, Scenario LLL for the Generation Fleet
V2G, LLL 0 0.4 M 0.8 M 1.2 M 1.6 M 2 M
Peak Winter 0 0 0 0 0 0
Peak Summer 0 0 0 0 0 0
Off-peak Winter 0 0.12 2.54 16.30 50.62 105.54
Off-peak Summer 0 0 0.04 0.62 5.28 24.44
Explaining How Market Curtailment Occurs
Figure 19.8 shows the offers to buy and sell
electricity in black and red, respectively, on one day
in the reference year Oct 2007–Sept 2008, together
with three other sets of offers to buy electricity in
gray. These were obtained by successively increasing
the amount to be bought. This is why the curves move
to the right. The day-ahead price in the reference year
was 32 euros. As more and more power is required,
the price rises, first to about 50 euros, then to about
100 euros. In the third case, the two curves no longer
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intersect, so no market fixing is possible. This is
called curtailment. It would happen if more power is
required to charge the batteries of the EVs than is
available. Exactly the same problem occurs if too
much power is taken from the batteries during peak
hours for sale, except that the offers to sell increase,
rather than the offers to buy.
It is assumed that buyers and sellers continue to use
the same strategies as in the reference year. In
practice they would probably change them.
Impact on the Average Price
During peak periods the average price drops in the V2G
scenario as the number of EVs increases, because more and
more power is drawn from the batteries of parked cars. The
average price drops from about 85 euros to about 75 euros for
2 million EVs. In off-peak periods additional power has to be
put into the batteries to compensate for the drawdown during
peak hours, so the average price is higher in the V2G
scenario. In winter, the average price rises to above 300 euros
both in the optimistic and the pessimistic generation
scenarios. This raises three questions. First would users
accept paying more in off-peak periods than in peak hours?
Second, how much power would smart meter operators be
prepared to offer to sell from the batteries, knowing that the
more they offer the lower the price will be? They would
probably optimize their offering strategy so as to maximize
their profits, to the detriment of EV users and consumers in
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general. Third, the increase in price will have a flow-on
impact on the balancing market (marché d'ajustement, in
French) run by the grid operator, RTE, because in order to
promote stability and security of supply on the grid the prices
are pegged relative to the day-ahead market. Higher prices on
the day-ahead market will therefore flow through the
balancing market to utilities.
Interpreting the Results on “Market Curtailment”
When the French government gave the grid operator, RTE,
the responsibility of evaluating the risk of not having enough
electricity over the forthcoming 10–15 years, its objective
9
was to ensure that the estimated shortfall would be kept to
socially and economically acceptable levels. The criterion
chosen is that the annual loss of load expectation (in hours)
should remain under three hours per year. Table 19.3 and
Table 19.4 show that market curtailment occurred
increasingly often in the simulations in off-peak periods with
and without the V2G option. In many cases the number of
hours exceeded the acceptability threshold prescribed by the
French government (3 hours per year). These results show
that if bidders continued to use the same strategies as in
2007–2008 for offering power on the bourse, market
curtailment would become increasingly common.
9
RTE, General Adequacy Report (2009) p. 12.
In a companion paper [19] it was shown that the market reacts
quite quickly to high prices. In the case studied, the day after
the price spike, larger quantities were offered for sale, albeit
at higher prices, from neighboring countries, which become
exporters rather than importers. So as long as these countries
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have excess power or are able to source it cheaper elsewhere,
then it is likely they will continue to divert power to France in
order to optimize profits. However, as the European Union is
pushing to reduce CO
2
emissions from transport and to rid
urban areas of gas-powered vehicles, Europe could reach a
point where there is no surplus capacity and market
curtailment could become a reality. Even if market players
adapt their bidding strategies to the changing situation, the
difference in consumption between peak and off-peak periods
will be attenuated. There will be far less need for additional
peak producers. Instead additional baseload capacity will be
required.
Conclusions
Most studies on the impact of wind power and of the
introduction of EVs on electricity prices have assumed that
the supply curve was equal to the full merit order and that
demand is inelastic. Armstrong et al. [19] demonstrated that
neither of these assumptions holds for the French day-ahead
market. The major contribution of this chapter is to propose a
method for modeling the offers to buy and selling power on
the wholesale market in the absence of such restrictive
hypotheses. Instead a method has been developed based on a
dataset of the observed aggregated offers to buy and sell
power on the bourse over a 12-month reference period from
October 2007 to September 2008.
The underlying hypothesis is that buyers and sellers will
continue to use the same strategies when making offers in the
future as they do today. One advantage of this approach is
that it generates pairs of aggregate offers that correspond to a
given set of conditions (availability of power stations,
weather, fuel prices, etc). In the long run further work is
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required to analyze bidding behavior, in particular to
determine how it changes during periods of stress.
Three factors that will be important in the future but that were
not taken into account in this study because they are too
recent are
• the market coupling between the French and German
electricity markets that took effect on November 9, 2010,
and so less than 12 months of data were available. Later on,
it would be interesting to repeat the study using the new
aggregate curves.
• the stochastic nature of wind power. When this study
started, the average wind availability (22%) was given in
the latest RTE reports [1] and [5], but information on its
day-to-day variability only started to be published in
January 2011. As with the aggregate curves after market
coupling, it will be very interesting to repeat the study
when a longer time series is available.
• a new law called the Loi Nome which has been passed by
the French parliament but has not yet been implemented (as
of June 1, 2011). It will allow retail sellers of electricity to
buy what they require directly from wholesalers through
long-term contracts. This will dry up the liquidity on the
market.
The next 10 years will be a dynamic and exciting period for
the electric system in France. Many changes will come into
effect: smart meters, 2 million new EVs, and large quantities
of wind power, in addition to the Loi Nome, a capacity
market, and the changes in the generation fleet that were
listed earlier. The electric system as a whole and the market
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may have trouble adapting to so many changes in such a short
period of time.
Acknowledgments
We would like to thank EpexSpot (formerly Powernext) for
allowing us to use the aggregate offers to buy and sell
electricity on the French day-ahead market. Thanks also to
Audrey Mahuet, Florence Very, and Aymen Salah Abou El
Enien of EpexSpot for answering our questions and to
Philippe Vassilopoulos for his comments and suggestions.
The opinions expressed here are those of the authors.
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